Key responsibilities include:

• Deriving and authoring safety requirements from system-level hazard analyses, functional hazard assessments, and customer/regulatory safety objectives.
• Translating safety requirements into clear, testable software requirements aligned with the appropriate Design Assurance Level (DAL) or software criticality classification.
• Maintaining bidirectional traceability from safety requirements through design, implementation, and verification.
• Collaborating with QA and test teams to define verification strategies, review test cases for safety coverage, and confirm that safety requirements are demonstrably satisfied prior to release.
• Authoring clear, well-structured safety documentation and contributing to system models (SysML/MBSE) with a safety lens.
• Leading and supporting safety analysis activities, including Functional Hazard Assessments (FHA), Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), and Failure Mode and Effects Summary (FMES).

The ideal candidate will have a Bachelor's degree with approximately 7+ years of relevant experience, or a Master's degree with approximately 5+ years of relevant experience, in Systems Engineering, Software Engineering, or a closely related technical field.

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The Hivemind Enterprise product is a software development kit (SDK) that enables scalable design, deployment, evaluation, and iteration of autonomy architectures for a wide range of robotic platforms.

As a Systems Modeler for Hivemind at Shield AI, you will be a key member of a multidisciplinary Systems Engineering team, working collaboratively with Product, technical individual contributors, and Test / Quality Assurance team members to define, model, and communicate the structure and behavior of complex autonomy software systems.

This role focuses on building and maintaining system models that span the full product stack,from foundational software and autonomy algorithms to developer infrastructure to user-facing interfaces.

In addition to modeling the Hivemind SDK product, you will also use your skills to help us improve our internal engineering processes, modeling the design of the systems that support product development such as CI/CD pipelines, test and configuration systems, and software and product life cycle processes.

While your primary focus will be systems modeling, as part of a full Systems Engineering team, you will also support your team members as needed by helping with functions such as requirements development.

This role is hands-on and highly collaborative, requiring deep expertise in systems modeling and Model-Based Systems Engineering (MBSE), strong software system intuition, and working knowledge of autonomous software pipelines.

As a Systems Modeler on the Hivemind team, you will help create a shared, rigorous understanding of one of Shield AI’s most complex and critical software products.

Your models will shape architecture decisions, enable cross-team alignment, and ensure that Hivemind continues to scale as a robust autonomy platform.

WHAT YOU'LL DO:

System modeling and MBSE: Develop and maintain high-quality system models that describe architecture, behavior, interfaces, and data flows across the Hivemind SDK.

Cross-stack system understanding: Work closely with engineers across the entire product stack,including foundational software, autonomy and AI algorithms, simulation and test infrastructure, and GUI layers,to capture an accurate and fully detailed model of the Hivemind SDK product.

Process and lifecycle modeling: Model internal engineering processes such as software development lifecycle workflows, CI/CD pipelines, testing and release processes, and configuration management to improve shared understanding and enable continuous improvement.

Architecture definition and analysis: Support system architecture trade studies, identify dependencies and constraints, and analyze impacts of design decisions across software components, development workflows, and operational use cases.

Requirements support: Ensure alignment and traceability between requirements and system models.

Communication and documentation: Use system models as a primary communication artifact to align stakeholders, surface risks and gaps, and enable informed technical decision-making across teams.

REQUIRED QUALIFICATIONS:

• Bachelor’s degree with approximately 7+ years of relevant experience, or Master’s degree with approximately 5+ years of relevant experience, in Systems Engineering, Aerospace Engineering, Robotics, Software Engineering, or a closely related technical field with demonstrated experience working on complex software or autonomous systems.

• Strong experience with MBSE practices, including practical application of SysML v1.6 and familiarity with SysML v2 concepts.

• Hands-on experience with Cameo Systems Modeler or equivalent MBSE tools.

• Proven ability to understand, model, and reason about large-scale autonomy software systems and developer-focused SDKs.

• Strong understanding of modern software engineering practices, including CI/CD, automated testing, configuration management, and software lifecycle processes.

• Experience working cross-functionally with software engineers, autonomy / AI engineers, test engineers, product managers, and UX / GUI teams.

• Familiarity with requirements engineering concepts (e.g., requirement quality, traceability, validation) and willingness to contribute to requirements writing when needed.

• Familiarity with software development workflows in modern languages (C++17 or later, Python, Go, etc.).

PREFERRED QUALIFICATIONS:

• Prior experience modeling autonomy or robotic systems.

• Experience supporting or defining developer tooling, SDKs, or platforms.

• Exposure to safety-critical or mission-critical software development environments.

• Experience using system models to drive reviews, design milestones, or technical decision forums.

• Experience creating software tooling. For example, scripts to import information into Cameo.

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The Hivemind Enterprise product is a software development kit (SDK) that enables scalable design, deployment, evaluation, and iteration of autonomy architectures for a wide range of robotic platforms.

As a Requirements Engineer for Hivemind at Shield AI, you will be a key member of a multidisciplinary systems engineering team, working collaboratively with Product, technical individual contributors, Test / Quality Assurance team members, and systems modelers to translate product user stories into clear engineering requirements with testable metrics.

This role involves defining, modeling, and validating the Hivemind software system and its applications. It is hands-on and highly collaborative, requiring expertise in requirements formulation, traceability, management, systems modeling, and knowledge of autonomous software pipelines.

Responsibilities:

• Work cross-functionally with Product Managers, technical individual contributors, and Quality Assurance team members to translate high-level customer feature requests into clear, detailed technical requirements aligned with product vision and roadmap.

• Identify dependencies, constraints, edge cases, and risks within proposed product or technical requirements.

• Author clear and well-structured documentation, including acceptance criteria, traceability links, and system models.

• Collaborate with the Quality Assurance, Test, and development teams to validate that requirements are implemented correctly.

• Track and manage requirements throughout the development lifecycle.

• Serve as the point of integration between customer intent and engineering execution.

Qualifications:

• Bachelor’s degree with approximately 7+ years of relevant experience, or Master’s degree with approximately 5+ years of relevant experience, in Systems Engineering, Aerospace Engineering, Robotics, Software Engineering, or a closely related technical field.

• Extensive experience generating product and test requirements for software products.

• Working knowledge of requirements management tools such as DOORS, Jama, or Jira.

• Comprehensive understanding of robotics and autonomy concepts.

• Strong understanding of modern software engineering practices, including CI/CD, automated testing, configuration management, and software lifecycle processes.

Preferred Qualifications:

• Experience supporting or defining developer tooling, SDKs, or platforms.

• Exposure to safety-critical or mission-critical software development environments.

• Experience creating software tooling or using software APIs for common requirements and project management tools.

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